class_docstr: Class for a random batch method. The first element of the batch is selected by optimizing the acquisition in a standard way. The remaining elements are
  selected uniformly random in the domain of the objective.
  
  :param acquisition: acquisition function to be used to compute the batch.
  :param batch size: the number of elements in the batch.
code: def get_anchor_points(
      self, duplicate_manager=None, context_manager=None
  ):
      design_type, unique = "random", False
      if duplicate_manager:
          unique = True
  
      anchor_points_generator = RandomAnchorPointsGenerator(
          self.space, design_type
      )
      return anchor_points_generator.get(
          num_anchor=self.num_anchor,
          duplicate_manager=duplicate_manager,
          unique=unique,
          context_manager=self.acquisition.optimizer.context_manager,
      )
  
file_path: GPyOpt/GPyOpt/core/evaluators/batch_random.py
imports: from .base import SamplingBasedBatchEvaluator
  from ...optimization.anchor_points_generator import RandomAnchorPointsGenerator
  import numpy
label_desc: Use image node_id 3 for calling the RandomBatch obj's underlying member method code with example usage: obj.get_anchor_points(duplicate_manager, context_manager) and returns: anchor_points_generator